Identifying controlling features of engineering design iteration
Management Science
A model-based framework to overlap product development activities
Management Science - Special issue on frontier research in manufacturing and logistics
Time-Cost Trade-Offs in Overlapped Product Development
Operations Research
Advanced Engineering Informatics
Optimization of product development process based on multi-agent simulation
CDVE'09 Proceedings of the 6th international conference on Cooperative design, visualization, and engineering
Advances in Engineering Software
Engineering Applications of Artificial Intelligence
Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm
Computers and Industrial Engineering
Process planning for collaborative product development with CD-DSM in optoelectronic enterprises
Advanced Engineering Informatics
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A process simulation based method for scheduling product design change propagation
Advanced Engineering Informatics
Robotics and Computer-Integrated Manufacturing
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Overlapping and iteration between development activities are the main reasons to cause complexity in product development (PD) process. Overlapping may not only reduce duration of a project but also create rework risk, while iteration increases the project duration and cost. In order to balance the duration and cost, this article presents four types of time models from the angle of time overlapping and activities dependent relationships based on Collaboration Degree Design Structure Matrix (CD-DSM) and builds the cost model considering the negation cost. On basis of the formulated model, a hybridization of the Pareto genetic algorithm (PGA) and variable neighborhood search (VNS) algorithm is proposed to solve the bi-objective process optimization problem of PD project for reducing the project duration and cost. The VNS strategy is implemented after the genetic operation of crossover and mutation to improve the exploitation ability of the algorithm. And then, an industrial example, a LED module PD project in an optoelectronic enterprise, is provided to illustrate the utility of the proposed approach. The optimization model minimizes the project duration and cost associated with overlapping and iteration and yields a Pareto optimal solution of project activity sequence for project managers to make decision following different business purposes. The simulation results of two different problems show that the proposed approach has a good convergence and robustness.